diff --git a/action-graphics.Rmd b/action-graphics.Rmd index e35399c..7c9c2c9 100644 --- a/action-graphics.Rmd +++ b/action-graphics.Rmd @@ -156,7 +156,7 @@ Another way to use `nearPoints()` is with `allRows = TRUE` and `addDist = TRUE`. That will return the original data frame with two new columns: - `dist_` gives the distance between the row and the event (in pixels). -- `selected_` says whether or not it's near the click event (i.e. whether or not its a row that would be returned when `allRows = FALSE)`. +- `selected_` says whether or not it's near the click event (i.e. whether or not it's a row that would be returned when `allRows = FALSE)`. We'll see an example of that a little later. diff --git a/basic-ui.Rmd b/basic-ui.Rmd index 4946718..24b330b 100644 --- a/basic-ui.Rmd +++ b/basic-ui.Rmd @@ -452,7 +452,7 @@ These require new techniques in the server function, so we'll come back to that d. `renderText(str(lm(mpg ~ wt, data = mtcars)))` 2. Re-create the Shiny app from Section \@ref(plots), this time setting height to 300px and width to 700px. - Set the plot "alt" text so that a visually impaired user can tell that its a scatterplot of five random numbers. + Set the plot "alt" text so that a visually impaired user can tell that it's a scatterplot of five random numbers. 3. Update the options in the call to `renderDataTable()` below so that the data is displayed, but all other controls are suppressed (i.e., remove the search, ordering, and filtering commands). You'll need to read `?renderDataTable` and review the options at . diff --git a/reactivity-escaping.Rmd b/reactivity-escaping.Rmd index 5aaa493..89bf741 100644 --- a/reactivity-escaping.Rmd +++ b/reactivity-escaping.Rmd @@ -70,7 +70,7 @@ None of these actions change the reactive graph, so it remains as in Figure \@re ## Case studies -Next, lets take a look at a few useful cases where you might combine `reactiveValues()` and `observeEvent()` or `observe()` to solve problems that are otherwise very challenging (if not impossible). +Next, let's take a look at a few useful cases where you might combine `reactiveValues()` and `observeEvent()` or `observe()` to solve problems that are otherwise very challenging (if not impossible). These are useful templates for your own apps. ### One output modified by multiple inputs diff --git a/reactivity-foundations.Rmd b/reactivity-foundations.Rmd index 44c0189..c305b26 100644 --- a/reactivity-foundations.Rmd +++ b/reactivity-foundations.Rmd @@ -63,7 +63,7 @@ b2$x We'll come back to why you might create your own reactive values in Chapter \@ref(reactivity-components). Otherwise, most of the reactive values you'll encounter will come from the `input` argument to the server function. -These are a little different to the `reactiveValues()` that you create yourself because they're read-only: you're can't modify the values because Shiny automatically updates them based on user actions in the browser. +These are a little different to the `reactiveValues()` that you create yourself because they're read-only: you can't modify the values because Shiny automatically updates them based on user actions in the browser. ### Exercises